Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017

PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 p...

Full description

Bibliographic Details
Main Authors: Yazhu Wang, Xuejun Duan, Lei Wang
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/16/6/985
id doaj-adc803e96c1a460fa9621e49b6544e67
record_format Article
spelling doaj-adc803e96c1a460fa9621e49b6544e672020-11-25T02:56:09ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012019-03-0116698510.3390/ijerph16060985ijerph16060985Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017Yazhu Wang0Xuejun Duan1Lei Wang2Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaNanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaNanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaPM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM2.5 concentration changes. The results are as follows: (1) The annual average value of PM2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m3) regulated by Chinese government. PM2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.http://www.mdpi.com/1660-4601/16/6/985PM2.5 concentrationspatial-temporal evolutionsocioeconomic influence factorsChina
collection DOAJ
language English
format Article
sources DOAJ
author Yazhu Wang
Xuejun Duan
Lei Wang
spellingShingle Yazhu Wang
Xuejun Duan
Lei Wang
Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
International Journal of Environmental Research and Public Health
PM2.5 concentration
spatial-temporal evolution
socioeconomic influence factors
China
author_facet Yazhu Wang
Xuejun Duan
Lei Wang
author_sort Yazhu Wang
title Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
title_short Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
title_full Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
title_fullStr Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
title_full_unstemmed Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017
title_sort spatial-temporal evolution of pm2.5 concentration and its socioeconomic influence factors in chinese cities in 2014–2017
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2019-03-01
description PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM2.5 concentration changes. The results are as follows: (1) The annual average value of PM2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m3) regulated by Chinese government. PM2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.
topic PM2.5 concentration
spatial-temporal evolution
socioeconomic influence factors
China
url http://www.mdpi.com/1660-4601/16/6/985
work_keys_str_mv AT yazhuwang spatialtemporalevolutionofpm25concentrationanditssocioeconomicinfluencefactorsinchinesecitiesin20142017
AT xuejunduan spatialtemporalevolutionofpm25concentrationanditssocioeconomicinfluencefactorsinchinesecitiesin20142017
AT leiwang spatialtemporalevolutionofpm25concentrationanditssocioeconomicinfluencefactorsinchinesecitiesin20142017
_version_ 1724714028983386112